Embedded machine learning is possible with the Java Optimized Processor. It is an implementation of a Java virtual machine in hardware using FPGA technology. Furthermore, this processor and the associated tools allow hard real-time analysis of Java machine learning code. It is possible to obtain tight upper bounds on the number of CPU cycles a given section of code takes to execute.
We show how a support vector machine can be trained on a multicore
processor.

The project has many examples of how machine learning code in Java can be used on this processor. The chosen examples are from the support vector family of algorithms. Java is a popular language for practical implementation of machine learning environments.